AIMC Topic: Deep Learning

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An integrated three-stream network model for discriminating fish feeding intensity using multi-feature analysis and deep learning.

PloS one
Feed costs constitute a significant part of the expenses in the aquaculture industry. However, feeding practices in fish farming often rely on the breeder's experience, leading to feed wastage and environmental pollution. To achieve precision in feed...

DPNet: Scene text detection based on dual perspective CNN-transformer.

PloS one
With the continuous advancement of deep learning, research in scene text detection has evolved significantly. However, complex backgrounds and various text forms complicate the task of detecting text from images. CNN is a deep learning algorithm that...

IPCT-Net: Parallel information bottleneck modality fusion network for obstructive sleep apnea diagnosis.

Neural networks : the official journal of the International Neural Network Society
Obstructive sleep apnea (OSA) is a common sleep breathing disorder and timely diagnosis helps to avoid the serious medical expenses caused by related complications. Existing deep learning (DL)-based methods primarily focus on single-modal models, whi...

A systematic review of generalization research in medical image classification.

Computers in biology and medicine
Numerous Deep Learning (DL) classification models have been developed for a large spectrum of medical image analysis applications, which promises to reshape various facets of medical practice. Despite early advances in DL model validation and impleme...

A deep learning-based, real-time image report system for linear EUS.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The integrity of image acquisition is critical for biliopancreatic EUS reporting, significantly affecting the quality of EUS examinations and disease-related decision-making. However, the quality of EUS reports varies among endos...

Grading of diabetic retinopathy using a pre-segmenting deep learning classification model: Validation of an automated algorithm.

Acta ophthalmologica
PURPOSE: To validate the performance of autonomous diabetic retinopathy (DR) grading by comparing a human grader and a self-developed deep-learning (DL) algorithm with gold-standard evaluation.

The Impact of Deep Learning on Determining the Necessity of Bronchoscopy in Pediatric Foreign Body Aspiration: Can Negative Bronchoscopy Rates Be Reduced?

Journal of pediatric surgery
INTRODUCTION: This study aimed to evaluate the role of deep learning methods in diagnosing foreign body aspiration (FBA) to reduce the frequency of negative bronchoscopy and minimize potential complications.

Fractional-order stochastic gradient descent method with momentum and energy for deep neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel fractional-order stochastic gradient descent with momentum and energy (FOSGDME) approach is proposed. Specifically, to address the challenge of converging to a real extreme point encountered by the existing fractional gradient ...

Imaging pollen using a Raspberry Pi and LED with deep learning.

The Science of the total environment
The production of low-cost, small footprint imaging sensor would be invaluable for airborne global monitoring of pollen, which could allow for mitigation of hay fever symptoms. We demonstrate the use of a white light LED (light emitting diode) to ill...

Multimodal radiomics and deep learning models for predicting early femoral head deformity in LCPD.

European journal of radiology
PURPOSE: To develop a predictive model combining clinical, radiomic, and deep learning features based on X-ray and MRI to identify risk factors for early femoral head deformity in Legg-Calvé-Perthes disease (LCPD).